Link prediction in complex networks aims to infer potential future connections between the nodes by analyzing the network’s current structure and its past evolution. Over the past decade, this challenge has attracted significant research interest across different scientific fields, including LBD. Complex networks are dynamic evolving structures that change over time by adding new nodes or by forming new connections between the existing nodes. In the context of knowledge representation, these nodes can be understood as individual concepts or pieces of information, whereas the links between them represent the established relationships, associations, or interactions that connect these concepts. In this chapter, we study link prediction in the context of closed LBD. Section 8.1 presents the background for using network analysis and link prediction for LBD. Section 8.2 presents a specific link prediction approach to LBD. The chapter concludes with a discussion in Section 8.3, followed by presenting selected sources and code reuse in Section 8.4.